Dealing with missing data using the Heckman selection model: methods primer for epidemiologists-Reference-Cited by-同舟云学术

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Dealing with missing data using the Heckman selection model: methods primer for epidemiologists

Published:2023-01-04 Issue:1 Volume:52 Page:5-13
ISSN:0300-5771
Container-title:International Journal of Epidemiology
language:en
Short-container-title:

Author:

Muñoz Johanna¹^ORCID,Hufstedler Heather²^ORCID,Gustafson Paul³^ORCID,Bärnighausen Till²,De Jong Valentijn M T¹⁴^ORCID,Debray Thomas P A¹^ORCID

Affiliation:

1. Julius Centre for Health Sciences and Primary Care, Utrecht Medical Center , Utrecht, The Netherlands

2. Heidelberg Institute of Global Health, Universitätsklinikum Heidelberg , Heidelberg, Germany

3. Department of Statistics, University of British Columbia , Vancouver, BC, Canada

4. Data Analytics and Methods Task Force, European Medicines Agency , Amsterdam, The Netherlands

Funder

European Union’s Horizon 2020 Framework Programme

Publisher

Oxford University Press (OUP)

Subject

General Medicine,Epidemiology

Link

https://academic.oup.com/ije/article-pdf/52/1/5/49127171/dyac237.pdf

Reference30 articles.

1. Review: a gentle introduction to imputation of missing values;Donders;J Clin Epidemiol,2006

2. Inference and missing data;Rubin;Biometrika,1976

3. Selection models and pattern-mixture models to analyse longitudinal quality of life data subject to drop-out;Michiels;Stat Med,2002

4. Generalized shared-parameter models and missingness at random;Creemers;Stat Model,2011

5. Estimating models with sample selection bias: a survey;Vella;J Hum Resour,1998

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